Inverse transfer path analysis, a different approach to shorten time in NVH assessments

This paper presents the design and implementation of a simplified method, based on the transmissibility concept, for a noise path assessment, which allows a rapid and accurate analysis. The Inverse Transfer Path Analysis aims to assess, and determine, the contribution of the critical paths, which are transmitting structure-borne noises and vibrations, from the vehicle’s vibration sources to the driver’s ear. The cabin noise transfer function, from the involved attachment points and directions, can be simultaneously obtained by applying an impulsive noise source inside the cabin. This approach avoids the use of other time consuming classic procedures. The proposed methodology includes two types of tests, static condition tests in a semi-anechoic chamber and operational tests on a roller bench. The results assessment comprises the analysis of the noise contribution of each path, depending on the frequency and the vehicle speed range. This publication introduces a novel NVH method proposed to study and identify noise transfer paths in a car structure. The theoretical approach of the methodology, practical implementation, and obtained results, are described in this work, as well as a methodology validation, to evidence the suitability of the proposed method

An alternative close-proximity test to evaluate sound power level emitted by a rolling tyre

The noise emission of a rolling tyre is produced by different physical mechanisms generated during the tyre-road interaction, being the main noise source of a vehicle when driving at high speeds. Diverse measurement methods can be found in the literature to assess the rolling noise emission. In that sense, the close-proximity (CPX) method allows to evaluate tyre/road sound level with at least two microphones operating in the close field of the test tyre. This paper presents a new methodology, based on the CPX method, which allows assessing the sound power level of the rolling tyre by introducing some changes in the traditional close-proximity test. The methodology (named A-CPX) has been analytically and experimentally validated, and is finally used to obtain the total tyre/road sound power level emitted by the whole set of tyres of a vehicle

Gear sound model for an approach of a Mechanical Acoustic Vehicle Alerting System (MAVAS) to increase EV’s detectability

Hybrid-electric and electric vehicles significantly reduce noise road emissions. This noise mitigation also causes a reduction in the sound detectability and therefore it increases the potential of causing accidents. A suitable solution arises with the Acoustic Vehicle Alerting Systems (AVAS) emitting a warning sound to alert pedestrians about the presence of a silent vehicle. This paper details an acoustic prediction model capable of simulating the sound produced by a pair of spur dry gears used as a Mechanical Acoustic Vehicle Alerting System (MAVAS). This proposal that tries to reproduce a sound closer to the mechanical sound of a conventional vehicle would be used as an alternative to existing systems. The prediction model developed is validated and consists in two consecutive parts: first, a dynamic model studies the rattle of the gears, then, an analytical model reproduces the sound of each impact of the gear teeth. This sound model makes it possible to characterize a proposed gear combination of the MAVAS, verifying its compliance with the European legislation

A methodology for the extrapolation of coast-by noise of tyres from sound power level measurements

Traffic noise is one of the most predominant noise sources that affect citizens’ quality of life in urban areas. The increasing presence of alternative powered vehicles, such as electric or hybrid vehicles, could provide an improvement of such a situation due to the absence of internal combustion engines. However, tyre/road noise is independent of the vehicle type and still exists in alternative powered vehicles. Hence, efforts should focus also on reducing noise emission by means of new tyre designs. The tyre/road noise emission of newly produced tyres is currently evaluated by the Coast-By method, and as a result the rolling sound pressure level at the measuring distance, located 7.5 m away from the test vehicle is obtained. Such an acoustic index provides a very representative data of the annoyance that a pedestrian located at such distance could suffer. However, this value could be affected by external factors, such as environmental conditions. For that reason, this paper presents a methodology for extrapolating the sound pressure levels that are obtained in a Coast-By test, by means of the sound power level emitted by the specific tyre/road combination evaluated. This methodology could serve as the basis for defining a universal model to evaluate a tyre when rolling on a road, by using its sound power emission and predicting the Coast-By sound pressure level

Numerical sound prediction model to study tyre impact noise

Impact noise is one of the mechanisms of vibratory origin that constitutes tyre/road interaction noise. When assessing a vehicle as a noise source, the impact sound mechanism is especially significant when obstacles are present on the driving surface. This document aims to enhance understanding of the impact noise phenomenon by presenting a two-step numerical model for studying the sound propagation of an accelerated tyre impacting a flat, rigid, and reflective surface: Firstly, a dynamic analysis of the contact is performed using the Finite Element Method. Then, the Boundary Element Method is used to perform an acoustic analysis with the vibration of the tyre surface as the sound source. The model has been successfully validated through a drop-test, where a tyre/rim assembly is dropped onto a ground surface. The validation was determined by comparing the predicted Sound Pressure Level measurements to those obtained from a circular microphone structure at various points during the drop-test

Acoustic Directivity and Detectability of Electric Powered Two-Wheelers

Since motorcycles are one of the main sources of noise in urban environments, the use of electric powered two-wheelers may contribute to the improvement of soundscapes in Smart Cities. However, quiet vehicles can lead to an increased risk of accident for pedestrians and other drivers. In order to assess the noise generated by powered two-wheelers and their detectability, five different low capacity motorcycles were measured in a pass-by noise test. The measurements were performed at different speeds using a linear microphone array and a dummy head. The sound directivity radiated by the moving sources was studied with a microphone array. To establish the detectability of powered two-wheelers, thirty-seven subjects participated in an auditory test consisting on a virtual road-crossing scenario. The subjects had to detect the approaching of a vehicle at 20 km/h. The results showed a significant reduction in the sound pressure level emitted by electric motorcycles at low-speed, as well as a notable increase in sound directivity with velocity. The reaction time obtained for the detection of electric powered two-wheelers was higher compared to the traditional propulsion ones. The results highlighted the risk posed by this kind of electric vehicles for pedestrians

Assessment of warning sound detectability for electric vehicles by outdoor tests

Electric Vehicles (EV) are characterized by a high reduction of the acoustic emission. The absence of warning sounds entails a risk situation for pedestrians. The previous research is focused on detectability of warning sounds in different noise environments. These experiments are performed indoors, where a pedestrian’s conditions are not similar to real road crossing. Drivers’ behaviour study demonstrated that different environments and workload have influence on reaction time. Consequently, this paper proposes a methodology for the analysis of detectability of real warning sound using a dynamic subject. The sample was composed by 65 participants walking around a pedestrian area. Participants had to react when they detected a vehicle approaching. The subject’s response was affected by background noise, therefore, this parameter was measured. The results establish that power levels have influence on the detectability. There is an optimum power level which improves efficiency of vehicle detection. Besides, warning sound features and learning effect, based on previous experience, have influence on subject response

Study of the effectiveness of electric vehicle warning sounds depending on the urban environment

Electric and Hybrid Electric vehicles (EV and HEV) seem to be the future of transport in smart cities and the key for the total reduction of noise disturbance and pollution in urban areas. However, several problems have to be solved to guarantee the safety of these types of vehicle. Up to now, the use of HEV has shown the dangers of a “quiet” transport system in urban environments; in fact, it has been estimated that an HEV is twice as likely to be involved in a pedestrian crash as would be an internal combustion engine (ICE) vehicle in the same situation. With the aim of improving their safety, different kinds of warning sounds are being designed to increase the detectability of EV and HEV without themselves becoming new annoying sound sources. The sound directivity, frequency of emission and intensity of warning sound systems will guarantee their efficiency and limited noise impact. Several research works bring to the fore a significant variation of the pedestrian response time to different acoustic stimuli. However, it is necessary to examine the suitability of these warning sounds according to the urban environments in which they are going to be emitted. Distinct areas inside the city have different soundscapes whose spectral content can vary significantly, masking some of the sounds suggested as an alert. This paper analyses in detail the main characteristics of several warning sounds proposed by the industry, conducting a comparative study of the different design trends. A total of 131 sighted listeners were exposed to a virtual road-crossing test. The behaviour and appropriateness of warning sounds are analysed depending on the urban environment. For this purpose, three clearly different soundscapes have been selected: stopped vehicles at a traffic light, a pedestrian shopping area and the vicinity of a playground. The results highlight the wide variability in pedestrian reaction time for the different warning sounds used. Some signals considerably improve the detectability of the vehicle, providing results even above the ICE vehicle ones. However, other warning sounds do not decrease the reaction time with respect to the EV. In addition, a clear dependence is observed between the detectability and the soundscape involved, changing the results for the same warning sound depending on the acoustic environment.This work was carried out with funding from the General Directorate of Traffic, Spanish Ministry of Interior, through project SPIP2014-01406 (Study and adequacy of warning sounds in electric vehicles)

Assessment of warning sound detectability for electric vehicles by outdoor tests

Electric Vehicles (EV) are characterized by a high reduction of the acoustic emission. The absence of warning sounds entails a risk situation for pedestrians. The previous research is focused on detectability of warning sounds in different noise environments. These experiments are performed indoors, where a pedestrian’s conditions are not similar to real road crossing. Drivers’ behaviour study demonstrated that different environments and workload have influence on reaction time. Consequently, this paper proposes a methodology for the analysis of detectability of real warning sound using a dynamic subject. The sample was composed by 65 participants walking around a pedestrian area. Participants had to react when they detected a vehicle approaching. The subject’s response was affected by background noise, therefore, this parameter was measured. The results establish that power levels have influence on the detectability. There is an optimum power level which improves efficiency of vehicle detection. Besides, warning sound features and learning effect, based on previous experience, have influence on subject response

Effect of daily oral administration of pentoxifylline (PTX, 30 mg⋅kg⁻¹, last 4 weeks) on high fructose high fat diet- induced insulin resistance (IR, 10% fructose in drinking water plus 25% unsaturated fat in diet, for 12 weeks) associated changes in left ventricle contractility index, cycle duration, systolic duration and diastolic duration.

<p>Values are expressed as the mean ± S.E of mean; N = 6–8 animals; No statistical difference has been detected by One Way ANOVA and Newman Keuls <i>post hoc</i> test.</p